Performance modelling of screening unit of paper manufacturing plant using Markovian approach and nature inspired algorithms

Purpose The key objective of the present study is to conduct a comprehensive analysis of the performance of the screening unit in the paper manufacturing plant through reliability, availability, maintainability and dependability (RAMD) metrics investigation. The screening unit comprises four subsystems, including a medium consistency pump, a screen unit, a cleaner unit and a decker unit, with each having its own unique characteristics and failure patterns. Failure and repair rates for each subsystem are assumed to follow exponential distributions. Design/methodology/approach The RAMD measures such as reliability, availability, mean time between failures, mean time to repair and dependability ratio are calculated for the system and individual subsystems. Furthermore, the impact of varying failure rates on system performance is analysed, revealing the sensitivity of the screening subsystem to changes in reliability metrics. By utilizing the Markov birth-death process, Chapman-Kolmogorov differential-difference equations are developed to model the behaviour of the screening unit. The nature-inspired algorithms genetic algorithm and particle swarm optimization are applied to predict the availability of the screening unit at various population sizes and the number of iterations. Findings It is observed that the screening unit achieved the optimal availability as 0.955755. The numerical and graphical results are derived to highlight the importance of the study. The study provides valuable insights for system designers to optimize the performance of the screening unit and enhance overall plant efficiency. Research limitations/implications The present model is developed under the concepts of exponentially distributed failure and repair rates, but in large-scale plants, the subsystems may reflect any other pattern. The other implication of present study is observed in the selection of nature inspired algorithms. Originality/value In the present investigation, an efficient stochastic model is proposed that combines the Markov process with a nature-inspired optimization algorithm to improve reliability and availability of the screening unit in the paper production facility. This hybrid approach marks a big step forward in RAMD research. It provides a strong framework for addressing real-world difficulties in paper manufacturing industrial systems.